Machine learning

Lec 4: Logistics Regression

Lec 2: Supervised Learning (Regression)

Lec 1: Introduction to Learning

West Coast ML State of AI - Part 2

Meta annonce LA FIN de l'ère ChatGPT (Y. Lecun avait raison)

Meta announces THE END of the ChatGPT era (Y. Lecun was right)

Irit Chelly - Consistent Amortized Clustering via Generative Flow Networks (Heb)

Hands-on Machine Learning -- Custom Models and Training with TensorFlow

AutoGrad Changed Everything (Not Transformers) [Dr. Jeff Beck]

MACLA memoria y aprendizaje continuo, Transferencia humano-robot, Problema y dato del problema

MACLA memory and continuous learning, human-robot transfer, problem and problem data

Bringing Your App to Life with Vertex AI and Cloud Run

Construire un RAG avec Chat GPT 5.2| Comprendre les embeddings & les PDF !

Step-by-Step RAG Setup | Vectors and Embeddings Explained GPT5.2

Модель кластеризации DBSCAN простыми словами | МАШИННОЕ ОБУЧЕНИЕ

DBSCAN Clustering Model in Simple Terms | Machine Learning

Ce RAG 2.0 SURPERFORME tous les autres (Workflow n8n GRATUIT)

This RAG 2.0 OUTPERFORMS all others (FREE n8n workflow)

[ИАД, осень 2025] Байесовский выбор моделей. Лекция 14: Байесовская оптимизация

[IAD, Fall 2025] Bayesian Model Selection. Lecture 14: Bayesian Optimization

The "Final Boss" of Deep Learning

MLT - Revision session 2_End term

MLT - Revision session 2_End term

MLP 25T3 EndTerm Revision

MLP 25T3 EndTerm Revision

L12 Unsupervised Learning K Means Clustering

L12 Unsupervised Learning K Means Clustering

L11 Classification Performance Metrics

L11 Classification Performance Metrics

VLA Models and the New Robotics

MLT - Revision session 1_End term

MLT - Revision session 1_End term

Inbar Seroussi - SGD Exact Dynamics in High-Dimension: Insights for Algorithm Design (Eng)

Exhaustive Symbolic Regression, or how to find the best function for your data

Exhaustive Symbolic Regression, or how to find the best function for your data

RL en pre-training, Subespacios universales en DNNs, Unsupervised Learning

RL in pre-training, Universal subspaces in DNNs, Unsupervised Learning

Keynote Address - Engineering Intelligence: Building Practical ML Systems

NeurIPS Summary and ML News

MLT - Week 11, 12 SWU

MLT - Week 11, 12 SWU

L10 Nonlinear & Multiclass Classification

L10 Nonlinear & Multiclass Classification

Tony Jebara: Discriminative Learning of Generative Models

Tong Zhang: Two Algorithms for Learning Sparse Representations

Lawrence K. Saul: Distance Metric Learning for Large Margin Classification

Jason Eisner: Hidden Markov Models

Dale Schuurmans: Convex Training Algorithms for Hard Machine Learning Problems

Corinna Cortes: Rational Kernels: A General Machine Learning Framework for the Analysis of Text,...

Zohar Ringel - A Heuristic for Feature Learning and Sample Complexity (Heb)

The Mathematical Foundations of Intelligence [Professor Yi Ma]

MLT - Week 12

MLT - Week 12

L9 Classification (Logistic Regression)

L9 Classification (Logistic Regression)

Building Synthetic Data Pipelines for Open Research and Scalable AI Development

PINN for Challenging Multiphase Flow Problems||Multi-Agent LLM for Intelligent Design ||Dec 12, 2025